STA 364 Spring 2025

Exam 2 Outline

This in-class exam is worth 100 points. The take-home is worth 100 points.

Outline

  1. Content in Exam 1 Outline HERE.

  2. ETS Models

  • Smoothing models with trend
  • Smoothing models with seasonality
  • Identifying when to use multiplicative models vs additive models
  • Comparing models
  • How ETS() auto selection function works.
  • Given the forecast variance formula, \(\hat{\sigma}_h\), calculate the prediction interval.
  1. ARIMA Models
  • Stationarity: Identify if a series is or is not stationary.
  • Differencing: What is it? What kinds? Why?
  • Backshift notation: What is it, and what does it do?
  • Autoregressive Models (AR): Conditions, how to fit, model equation.
  • Moving Average Models (MA): Conditions, how to fit, model equation.
  • ARIMA Models: Write out the specific equation using the general equation and a 𝑝,𝑑, and 𝑞 (small) idenifying the orders (\(p\) and \(q\)) by looking at a stationary series’s correlogram and PACF plot.
  • SARIMA Models: Same as ARIMA but with a season piece.
  • ARIMA vs ETA
  • ARIMA() function default algorithm.
  1. Overall
  • Fitting and comparing models on a test set
  • Forecasting with all models

Codebank

You can also find the take home exam codebank by clicking HERE.